Overview

Brought to you by YData

Dataset statistics

Number of variables18
Number of observations12330
Missing cells789
Missing cells (%)0.4%
Duplicate rows69
Duplicate rows (%)0.6%
Total size in memory1.5 MiB
Average record size in memory130.0 B

Variable types

Numeric14
Categorical2
Boolean2

Alerts

Dataset has 69 (0.6%) duplicate rowsDuplicates
Administrative is highly overall correlated with Administrative_DurationHigh correlation
Administrative_Duration is highly overall correlated with AdministrativeHigh correlation
BounceRates is highly overall correlated with ExitRatesHigh correlation
ExitRates is highly overall correlated with BounceRates and 1 other fieldsHigh correlation
Informational is highly overall correlated with Informational_DurationHigh correlation
Informational_Duration is highly overall correlated with InformationalHigh correlation
ProductRelated is highly overall correlated with ExitRates and 1 other fieldsHigh correlation
ProductRelated_Duration is highly overall correlated with ProductRelatedHigh correlation
VisitorType is highly imbalanced (59.9%)Imbalance
Informational_Duration has 199 (1.6%) missing valuesMissing
ProductRelated_Duration has 491 (4.0%) missing valuesMissing
Administrative has 5768 (46.8%) zerosZeros
Administrative_Duration has 5903 (47.9%) zerosZeros
Informational has 9699 (78.7%) zerosZeros
Informational_Duration has 9768 (79.2%) zerosZeros
ProductRelated_Duration has 722 (5.9%) zerosZeros
BounceRates has 5518 (44.8%) zerosZeros
PageValues has 9600 (77.9%) zerosZeros
SpecialDay has 11079 (89.9%) zerosZeros

Reproduction

Analysis started2024-07-26 00:57:42.795150
Analysis finished2024-07-26 00:59:06.049794
Duration1 minute and 23.25 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Administrative
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct27
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3151663
Minimum0
Maximum27
Zeros5768
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:06.215220image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile9
Maximum27
Range27
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3217841
Coefficient of variation (CV)1.4347929
Kurtosis4.7011462
Mean2.3151663
Median Absolute Deviation (MAD)1
Skewness1.9603572
Sum28546
Variance11.03425
MonotonicityNot monotonic
2024-07-26T00:59:06.655706image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0 5768
46.8%
1 1354
 
11.0%
2 1114
 
9.0%
3 915
 
7.4%
4 765
 
6.2%
5 575
 
4.7%
6 432
 
3.5%
7 338
 
2.7%
8 287
 
2.3%
9 225
 
1.8%
Other values (17) 557
 
4.5%
ValueCountFrequency (%)
0 5768
46.8%
1 1354
 
11.0%
2 1114
 
9.0%
3 915
 
7.4%
4 765
 
6.2%
5 575
 
4.7%
6 432
 
3.5%
7 338
 
2.7%
8 287
 
2.3%
9 225
 
1.8%
ValueCountFrequency (%)
27 1
 
< 0.1%
26 1
 
< 0.1%
24 4
 
< 0.1%
23 3
 
< 0.1%
22 4
 
< 0.1%
21 2
 
< 0.1%
20 2
 
< 0.1%
19 6
 
< 0.1%
18 12
0.1%
17 16
0.1%

Administrative_Duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct3335
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.818611
Minimum0
Maximum3398.75
Zeros5903
Zeros (%)47.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:07.148671image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7.5
Q393.25625
95-th percentile348.26637
Maximum3398.75
Range3398.75
Interquartile range (IQR)93.25625

Descriptive statistics

Standard deviation176.77911
Coefficient of variation (CV)2.1873564
Kurtosis50.556739
Mean80.818611
Median Absolute Deviation (MAD)7.5
Skewness5.615719
Sum996493.47
Variance31250.853
MonotonicityNot monotonic
2024-07-26T00:59:07.571225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5903
47.9%
4 56
 
0.5%
5 53
 
0.4%
7 45
 
0.4%
11 42
 
0.3%
6 41
 
0.3%
14 37
 
0.3%
9 35
 
0.3%
15 33
 
0.3%
10 32
 
0.3%
Other values (3325) 6053
49.1%
ValueCountFrequency (%)
0 5903
47.9%
1.333333333 1
 
< 0.1%
2 15
 
0.1%
3 26
 
0.2%
3.5 4
 
< 0.1%
4 56
 
0.5%
4.333333333 1
 
< 0.1%
4.5 2
 
< 0.1%
4.75 1
 
< 0.1%
5 53
 
0.4%
ValueCountFrequency (%)
3398.75 1
< 0.1%
2720.5 1
< 0.1%
2657.318056 1
< 0.1%
2629.253968 1
< 0.1%
2407.42381 1
< 0.1%
2156.166667 1
< 0.1%
2137.112745 1
< 0.1%
2086.75 1
< 0.1%
2047.234848 1
< 0.1%
1951.279141 1
< 0.1%

Informational
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50356853
Minimum0
Maximum24
Zeros9699
Zeros (%)78.7%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:07.835981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2701564
Coefficient of variation (CV)2.522311
Kurtosis26.932266
Mean0.50356853
Median Absolute Deviation (MAD)0
Skewness4.0364638
Sum6209
Variance1.6132973
MonotonicityNot monotonic
2024-07-26T00:59:08.065739image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 9699
78.7%
1 1041
 
8.4%
2 728
 
5.9%
3 380
 
3.1%
4 222
 
1.8%
5 99
 
0.8%
6 78
 
0.6%
7 36
 
0.3%
9 15
 
0.1%
8 14
 
0.1%
Other values (7) 18
 
0.1%
ValueCountFrequency (%)
0 9699
78.7%
1 1041
 
8.4%
2 728
 
5.9%
3 380
 
3.1%
4 222
 
1.8%
5 99
 
0.8%
6 78
 
0.6%
7 36
 
0.3%
8 14
 
0.1%
9 15
 
0.1%
ValueCountFrequency (%)
24 1
 
< 0.1%
16 1
 
< 0.1%
14 2
 
< 0.1%
13 1
 
< 0.1%
12 5
 
< 0.1%
11 1
 
< 0.1%
10 7
 
0.1%
9 15
0.1%
8 14
 
0.1%
7 36
0.3%

Informational_Duration
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct1241
Distinct (%)10.2%
Missing199
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean34.724502
Minimum0
Maximum2549.375
Zeros9768
Zeros (%)79.2%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:08.327981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile196.70833
Maximum2549.375
Range2549.375
Interquartile range (IQR)0

Descriptive statistics

Standard deviation141.65568
Coefficient of variation (CV)4.0794159
Kurtosis75.4941
Mean34.724502
Median Absolute Deviation (MAD)0
Skewness7.5440009
Sum421242.93
Variance20066.333
MonotonicityNot monotonic
2024-07-26T00:59:08.618401image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9768
79.2%
9 32
 
0.3%
6 25
 
0.2%
10 25
 
0.2%
7 25
 
0.2%
12 23
 
0.2%
16 22
 
0.2%
13 22
 
0.2%
8 21
 
0.2%
11 20
 
0.2%
Other values (1231) 2148
 
17.4%
(Missing) 199
 
1.6%
ValueCountFrequency (%)
0 9768
79.2%
1 3
 
< 0.1%
1.5 1
 
< 0.1%
2 11
 
0.1%
2.5 1
 
< 0.1%
3 16
 
0.1%
3.5 1
 
< 0.1%
4 17
 
0.1%
5 18
 
0.1%
5.5 3
 
< 0.1%
ValueCountFrequency (%)
2549.375 1
< 0.1%
2256.916667 1
< 0.1%
2252.033333 1
< 0.1%
2195.3 1
< 0.1%
2166.5 1
< 0.1%
2050.433333 1
< 0.1%
1949.166667 1
< 0.1%
1830.5 1
< 0.1%
1779.166667 1
< 0.1%
1778 1
< 0.1%

ProductRelated
Real number (ℝ)

HIGH CORRELATION 

Distinct311
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.731468
Minimum0
Maximum705
Zeros38
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:08.906469image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median18
Q338
95-th percentile109
Maximum705
Range705
Interquartile range (IQR)31

Descriptive statistics

Standard deviation44.475503
Coefficient of variation (CV)1.4016214
Kurtosis31.211707
Mean31.731468
Median Absolute Deviation (MAD)13
Skewness4.3415164
Sum391249
Variance1978.0704
MonotonicityNot monotonic
2024-07-26T00:59:09.602531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 622
 
5.0%
2 465
 
3.8%
3 458
 
3.7%
4 404
 
3.3%
6 396
 
3.2%
7 391
 
3.2%
5 382
 
3.1%
8 370
 
3.0%
10 330
 
2.7%
9 317
 
2.6%
Other values (301) 8195
66.5%
ValueCountFrequency (%)
0 38
 
0.3%
1 622
5.0%
2 465
3.8%
3 458
3.7%
4 404
3.3%
5 382
3.1%
6 396
3.2%
7 391
3.2%
8 370
3.0%
9 317
2.6%
ValueCountFrequency (%)
705 1
< 0.1%
686 1
< 0.1%
584 1
< 0.1%
534 1
< 0.1%
518 1
< 0.1%
517 1
< 0.1%
501 1
< 0.1%
486 1
< 0.1%
470 1
< 0.1%
449 1
< 0.1%

ProductRelated_Duration
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct9210
Distinct (%)77.8%
Missing491
Missing (%)4.0%
Infinite0
Infinite (%)0.0%
Mean1190.5349
Minimum0
Maximum63973.522
Zeros722
Zeros (%)5.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:09.899718image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1183.85417
median597.625
Q31462.5546
95-th percentile4291.09
Maximum63973.522
Range63973.522
Interquartile range (IQR)1278.7004

Descriptive statistics

Standard deviation1908.4477
Coefficient of variation (CV)1.603017
Kurtosis142.69356
Mean1190.5349
Median Absolute Deviation (MAD)499.25182
Skewness7.3945211
Sum14094743
Variance3642172.6
MonotonicityNot monotonic
2024-07-26T00:59:10.211573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 722
 
5.9%
17 19
 
0.2%
11 17
 
0.1%
15 16
 
0.1%
8 16
 
0.1%
12 15
 
0.1%
19 15
 
0.1%
7 14
 
0.1%
13 14
 
0.1%
22 14
 
0.1%
Other values (9200) 10977
89.0%
(Missing) 491
 
4.0%
ValueCountFrequency (%)
0 722
5.9%
0.5 1
 
< 0.1%
1 2
 
< 0.1%
2.333333333 1
 
< 0.1%
2.666666667 1
 
< 0.1%
3 4
 
< 0.1%
4 9
 
0.1%
5 12
 
0.1%
5.333333333 1
 
< 0.1%
6 5
 
< 0.1%
ValueCountFrequency (%)
63973.52223 1
< 0.1%
43171.23338 1
< 0.1%
29970.46597 1
< 0.1%
27009.85943 1
< 0.1%
24844.1562 1
< 0.1%
23888.81 1
< 0.1%
23342.08205 1
< 0.1%
23050.10414 1
< 0.1%
21672.24425 1
< 0.1%
18504.12621 1
< 0.1%

BounceRates
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1872
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02219138
Minimum0
Maximum0.2
Zeros5518
Zeros (%)44.8%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:10.511623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0031124675
Q30.016812558
95-th percentile0.2
Maximum0.2
Range0.2
Interquartile range (IQR)0.016812558

Descriptive statistics

Standard deviation0.048488322
Coefficient of variation (CV)2.185007
Kurtosis7.7231594
Mean0.02219138
Median Absolute Deviation (MAD)0.0031124675
Skewness2.9478553
Sum273.61972
Variance0.0023511174
MonotonicityNot monotonic
2024-07-26T00:59:10.817605image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5518
44.8%
0.2 700
 
5.7%
0.066666667 134
 
1.1%
0.028571429 115
 
0.9%
0.05 113
 
0.9%
0.033333333 101
 
0.8%
0.025 100
 
0.8%
0.016666667 99
 
0.8%
0.1 98
 
0.8%
0.04 96
 
0.8%
Other values (1862) 5256
42.6%
ValueCountFrequency (%)
0 5518
44.8%
2.73 × 10-51
 
< 0.1%
3.35 × 10-51
 
< 0.1%
3.83 × 10-51
 
< 0.1%
3.94 × 10-51
 
< 0.1%
7.09 × 10-51
 
< 0.1%
7.27 × 10-51
 
< 0.1%
7.5 × 10-51
 
< 0.1%
8.01 × 10-51
 
< 0.1%
8.08 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.2 700
5.7%
0.183333333 1
 
< 0.1%
0.18 5
 
< 0.1%
0.176923077 1
 
< 0.1%
0.175 1
 
< 0.1%
0.166666667 4
 
< 0.1%
0.164285714 1
 
< 0.1%
0.164230769 1
 
< 0.1%
0.161904762 1
 
< 0.1%
0.16 3
 
< 0.1%

ExitRates
Real number (ℝ)

HIGH CORRELATION 

Distinct4746
Distinct (%)38.8%
Missing99
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.04302104
Minimum0
Maximum0.2
Zeros74
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:11.125619image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.004545455
Q10.014285714
median0.025141026
Q30.05
95-th percentile0.2
Maximum0.2
Range0.2
Interquartile range (IQR)0.035714286

Descriptive statistics

Standard deviation0.048562171
Coefficient of variation (CV)1.1288005
Kurtosis4.0408925
Mean0.04302104
Median Absolute Deviation (MAD)0.014160149
Skewness2.1539196
Sum526.19035
Variance0.0023582844
MonotonicityNot monotonic
2024-07-26T00:59:11.437344image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2 704
 
5.7%
0.1 331
 
2.7%
0.05 327
 
2.7%
0.033333333 289
 
2.3%
0.066666667 267
 
2.2%
0.025 222
 
1.8%
0.04 214
 
1.7%
0.016666667 181
 
1.5%
0.02 166
 
1.3%
0.022222222 151
 
1.2%
Other values (4736) 9379
76.1%
ValueCountFrequency (%)
0 74
0.6%
0.000175593 1
 
< 0.1%
0.000250438 1
 
< 0.1%
0.000262123 1
 
< 0.1%
0.000263158 1
 
< 0.1%
0.000292398 1
 
< 0.1%
0.000409836 1
 
< 0.1%
0.000446429 1
 
< 0.1%
0.000468384 1
 
< 0.1%
0.000480769 1
 
< 0.1%
ValueCountFrequency (%)
0.2 704
5.7%
0.192307692 1
 
< 0.1%
0.188888889 2
 
< 0.1%
0.186666667 4
 
< 0.1%
0.183333333 2
 
< 0.1%
0.181818182 1
 
< 0.1%
0.18034188 1
 
< 0.1%
0.18 3
 
< 0.1%
0.177777778 5
 
< 0.1%
0.175 6
 
< 0.1%

PageValues
Real number (ℝ)

ZEROS 

Distinct2704
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8892579
Minimum0
Maximum361.76374
Zeros9600
Zeros (%)77.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:11.777468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile38.160528
Maximum361.76374
Range361.76374
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.568437
Coefficient of variation (CV)3.1529332
Kurtosis65.635694
Mean5.8892579
Median Absolute Deviation (MAD)0
Skewness6.3829642
Sum72614.549
Variance344.78684
MonotonicityNot monotonic
2024-07-26T00:59:12.061427image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9600
77.9%
53.988 6
 
< 0.1%
42.29306752 3
 
< 0.1%
59.988 2
 
< 0.1%
16.1585582 2
 
< 0.1%
44.89345937 2
 
< 0.1%
14.1273698 2
 
< 0.1%
34.03997536 2
 
< 0.1%
10.99901844 2
 
< 0.1%
58.9241766 2
 
< 0.1%
Other values (2694) 2707
 
22.0%
ValueCountFrequency (%)
0 9600
77.9%
0.038034542 1
 
< 0.1%
0.067049546 1
 
< 0.1%
0.093546949 1
 
< 0.1%
0.098621403 1
 
< 0.1%
0.120699914 1
 
< 0.1%
0.129676893 1
 
< 0.1%
0.131837013 1
 
< 0.1%
0.139200623 1
 
< 0.1%
0.150650498 1
 
< 0.1%
ValueCountFrequency (%)
361.7637419 1
< 0.1%
360.9533839 1
< 0.1%
287.9537928 1
< 0.1%
270.7846931 1
< 0.1%
261.4912857 1
< 0.1%
258.5498732 1
< 0.1%
255.5691579 1
< 0.1%
254.6071579 1
< 0.1%
246.7585902 1
< 0.1%
239.98 1
< 0.1%

SpecialDay
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.061427413
Minimum0
Maximum1
Zeros11079
Zeros (%)89.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:12.323380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.6
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.19891727
Coefficient of variation (CV)3.2382492
Kurtosis9.9136589
Mean0.061427413
Median Absolute Deviation (MAD)0
Skewness3.3026667
Sum757.4
Variance0.039568082
MonotonicityNot monotonic
2024-07-26T00:59:12.535209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 11079
89.9%
0.6 351
 
2.8%
0.8 325
 
2.6%
0.4 243
 
2.0%
0.2 178
 
1.4%
1 154
 
1.2%
ValueCountFrequency (%)
0 11079
89.9%
0.2 178
 
1.4%
0.4 243
 
2.0%
0.6 351
 
2.8%
0.8 325
 
2.6%
1 154
 
1.2%
ValueCountFrequency (%)
1 154
 
1.2%
0.8 325
 
2.6%
0.6 351
 
2.8%
0.4 243
 
2.0%
0.2 178
 
1.4%
0 11079
89.9%

Month
Categorical

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size96.5 KiB
May
3348 
Nov
2980 
Mar
1897 
Dec
1713 
Oct
545 
Other values (6)
1847 

Length

Max length4
Median length3
Mean length3.0233577
Min length3

Characters and Unicode

Total characters37278
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFeb
2nd rowFeb
3rd rowFeb
4th rowFeb
5th rowFeb

Common Values

ValueCountFrequency (%)
May 3348
27.2%
Nov 2980
24.2%
Mar 1897
15.4%
Dec 1713
13.9%
Oct 545
 
4.4%
Sep 446
 
3.6%
Aug 431
 
3.5%
Jul 429
 
3.5%
June 288
 
2.3%
Feb 183
 
1.5%

Length

2024-07-26T00:59:12.785470image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
may 3348
27.2%
nov 2980
24.2%
mar 1897
15.4%
dec 1713
13.9%
oct 545
 
4.4%
aug 501
 
4.1%
sep 446
 
3.6%
jul 429
 
3.5%
june 288
 
2.3%
feb 183
 
1.5%

Most occurring characters

ValueCountFrequency (%)
a 5315
14.3%
M 5245
14.1%
y 3348
9.0%
N 2980
8.0%
o 2980
8.0%
v 2980
8.0%
e 2630
7.1%
c 2258
 
6.1%
r 1897
 
5.1%
D 1713
 
4.6%
Other values (12) 5932
15.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37278
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 5315
14.3%
M 5245
14.1%
y 3348
9.0%
N 2980
8.0%
o 2980
8.0%
v 2980
8.0%
e 2630
7.1%
c 2258
 
6.1%
r 1897
 
5.1%
D 1713
 
4.6%
Other values (12) 5932
15.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37278
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 5315
14.3%
M 5245
14.1%
y 3348
9.0%
N 2980
8.0%
o 2980
8.0%
v 2980
8.0%
e 2630
7.1%
c 2258
 
6.1%
r 1897
 
5.1%
D 1713
 
4.6%
Other values (12) 5932
15.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37278
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 5315
14.3%
M 5245
14.1%
y 3348
9.0%
N 2980
8.0%
o 2980
8.0%
v 2980
8.0%
e 2630
7.1%
c 2258
 
6.1%
r 1897
 
5.1%
D 1713
 
4.6%
Other values (12) 5932
15.9%

OperatingSystems
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1240065
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:12.997431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile3
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.91132483
Coefficient of variation (CV)0.42905934
Kurtosis10.456843
Mean2.1240065
Median Absolute Deviation (MAD)0
Skewness2.066285
Sum26189
Variance0.83051294
MonotonicityNot monotonic
2024-07-26T00:59:13.208584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2 6601
53.5%
1 2585
 
21.0%
3 2555
 
20.7%
4 478
 
3.9%
8 79
 
0.6%
6 19
 
0.2%
7 7
 
0.1%
5 6
 
< 0.1%
ValueCountFrequency (%)
1 2585
 
21.0%
2 6601
53.5%
3 2555
 
20.7%
4 478
 
3.9%
5 6
 
< 0.1%
6 19
 
0.2%
7 7
 
0.1%
8 79
 
0.6%
ValueCountFrequency (%)
8 79
 
0.6%
7 7
 
0.1%
6 19
 
0.2%
5 6
 
< 0.1%
4 478
 
3.9%
3 2555
 
20.7%
2 6601
53.5%
1 2585
 
21.0%

Browser
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3570965
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:13.459702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile5
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7172767
Coefficient of variation (CV)0.72855594
Kurtosis12.746733
Mean2.3570965
Median Absolute Deviation (MAD)0
Skewness3.2423496
Sum29063
Variance2.9490392
MonotonicityNot monotonic
2024-07-26T00:59:13.705438image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2 7961
64.6%
1 2462
 
20.0%
4 736
 
6.0%
5 467
 
3.8%
6 174
 
1.4%
10 163
 
1.3%
8 135
 
1.1%
3 105
 
0.9%
13 61
 
0.5%
7 49
 
0.4%
Other values (3) 17
 
0.1%
ValueCountFrequency (%)
1 2462
 
20.0%
2 7961
64.6%
3 105
 
0.9%
4 736
 
6.0%
5 467
 
3.8%
6 174
 
1.4%
7 49
 
0.4%
8 135
 
1.1%
9 1
 
< 0.1%
10 163
 
1.3%
ValueCountFrequency (%)
13 61
 
0.5%
12 10
 
0.1%
11 6
 
< 0.1%
10 163
 
1.3%
9 1
 
< 0.1%
8 135
 
1.1%
7 49
 
0.4%
6 174
 
1.4%
5 467
3.8%
4 736
6.0%

Region
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1473642
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:13.924096image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4015912
Coefficient of variation (CV)0.76304842
Kurtosis-0.1486803
Mean3.1473642
Median Absolute Deviation (MAD)2
Skewness0.98354916
Sum38807
Variance5.7676405
MonotonicityNot monotonic
2024-07-26T00:59:14.134914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 4780
38.8%
3 2403
19.5%
4 1182
 
9.6%
2 1136
 
9.2%
6 805
 
6.5%
7 761
 
6.2%
9 511
 
4.1%
8 434
 
3.5%
5 318
 
2.6%
ValueCountFrequency (%)
1 4780
38.8%
2 1136
 
9.2%
3 2403
19.5%
4 1182
 
9.6%
5 318
 
2.6%
6 805
 
6.5%
7 761
 
6.2%
8 434
 
3.5%
9 511
 
4.1%
ValueCountFrequency (%)
9 511
 
4.1%
8 434
 
3.5%
7 761
 
6.2%
6 805
 
6.5%
5 318
 
2.6%
4 1182
 
9.6%
3 2403
19.5%
2 1136
 
9.2%
1 4780
38.8%

TrafficType
Real number (ℝ)

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0695864
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2024-07-26T00:59:14.385148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile13
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.0251692
Coefficient of variation (CV)0.98908557
Kurtosis3.4797106
Mean4.0695864
Median Absolute Deviation (MAD)1
Skewness1.9629867
Sum50178
Variance16.201987
MonotonicityNot monotonic
2024-07-26T00:59:14.613369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
2 3913
31.7%
1 2451
19.9%
3 2052
16.6%
4 1069
 
8.7%
13 738
 
6.0%
10 450
 
3.6%
6 444
 
3.6%
8 343
 
2.8%
5 260
 
2.1%
11 247
 
2.0%
Other values (10) 363
 
2.9%
ValueCountFrequency (%)
1 2451
19.9%
2 3913
31.7%
3 2052
16.6%
4 1069
 
8.7%
5 260
 
2.1%
6 444
 
3.6%
7 40
 
0.3%
8 343
 
2.8%
9 42
 
0.3%
10 450
 
3.6%
ValueCountFrequency (%)
20 198
 
1.6%
19 17
 
0.1%
18 10
 
0.1%
17 1
 
< 0.1%
16 3
 
< 0.1%
15 38
 
0.3%
14 13
 
0.1%
13 738
6.0%
12 1
 
< 0.1%
11 247
 
2.0%

VisitorType
Categorical

IMBALANCE 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size96.5 KiB
Returning_Visitor
10551 
New_Visitor
1694 
Other
 
85

Length

Max length17
Median length17
Mean length16.092944
Min length5

Characters and Unicode

Total characters198426
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReturning_Visitor
2nd rowReturning_Visitor
3rd rowReturning_Visitor
4th rowReturning_Visitor
5th rowReturning_Visitor

Common Values

ValueCountFrequency (%)
Returning_Visitor 10551
85.6%
New_Visitor 1694
 
13.7%
Other 85
 
0.7%

Length

2024-07-26T00:59:14.877778image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-26T00:59:15.154222image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
returning_visitor 10551
85.6%
new_visitor 1694
 
13.7%
other 85
 
0.7%

Most occurring characters

ValueCountFrequency (%)
i 35041
17.7%
t 22881
11.5%
r 22881
11.5%
n 21102
10.6%
e 12330
 
6.2%
_ 12245
 
6.2%
V 12245
 
6.2%
s 12245
 
6.2%
o 12245
 
6.2%
R 10551
 
5.3%
Other values (6) 24660
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 198426
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 35041
17.7%
t 22881
11.5%
r 22881
11.5%
n 21102
10.6%
e 12330
 
6.2%
_ 12245
 
6.2%
V 12245
 
6.2%
s 12245
 
6.2%
o 12245
 
6.2%
R 10551
 
5.3%
Other values (6) 24660
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 198426
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 35041
17.7%
t 22881
11.5%
r 22881
11.5%
n 21102
10.6%
e 12330
 
6.2%
_ 12245
 
6.2%
V 12245
 
6.2%
s 12245
 
6.2%
o 12245
 
6.2%
R 10551
 
5.3%
Other values (6) 24660
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 198426
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 35041
17.7%
t 22881
11.5%
r 22881
11.5%
n 21102
10.6%
e 12330
 
6.2%
_ 12245
 
6.2%
V 12245
 
6.2%
s 12245
 
6.2%
o 12245
 
6.2%
R 10551
 
5.3%
Other values (6) 24660
12.4%

Weekend
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
False
9462 
True
2868 
ValueCountFrequency (%)
False 9462
76.7%
True 2868
 
23.3%
2024-07-26T00:59:15.411606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Revenue
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
False
10422 
True
1908 
ValueCountFrequency (%)
False 10422
84.5%
True 1908
 
15.5%
2024-07-26T00:59:15.639693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Interactions

2024-07-26T00:59:00.255878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:46.639093image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:59.284962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:10.365171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:17.813851image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:21.653318image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:26.452621image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:30.372850image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:34.067238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:39.313782image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:44.039174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:47.680676image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:51.810929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:56.469831image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:00.509405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:47.717701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:59.856527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:11.362433image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:18.077062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:22.055662image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:26.715719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:30.627810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:34.317416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:40.153698image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:44.293616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:47.939257image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:52.196802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:56.732106image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:00.778396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:48.986358image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:00.569767image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:11.930237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:18.328897image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:22.450542image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:26.983950image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:30.892452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:34.595032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:40.589858image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:44.544369image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:48.234501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:52.583113image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:57.005458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:01.044445image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:49.870659image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:00.913674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:12.222513image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:18.578074image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:22.813611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:27.262161image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:31.150187image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:34.860237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:41.038389image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:44.794520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:48.494353image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:52.947462image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:57.260012image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:01.289396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:50.751627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:01.249049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:12.694067image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:18.826150image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:23.168368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:27.506947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:31.412272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:35.132756image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:41.361007image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:45.047561image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:48.762688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:53.314953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:57.513205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:01.561109image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:51.547379image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:01.780042image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:13.332141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:19.284197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:23.538110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:27.763206image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:31.678277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:35.446747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:41.618562image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:45.304493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:49.036511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:54.142660image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:57.793723image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:01.836959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:52.543923image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:02.846753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:13.914948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:19.533900image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:23.908231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:28.028199image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:31.935685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:35.801805image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:41.884732image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:45.555812image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:49.320153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:54.418938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:58.064010image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:02.104649image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:53.593825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:04.433444image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:14.571799image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:19.810247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:24.272382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:28.518362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:32.203394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:36.198562image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:42.185916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:45.826609image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:49.592396image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:54.696657image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:58.356236image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:02.372224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:54.556905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:05.413701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:15.094882image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:20.100021image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:24.701806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:28.788443image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:32.486744image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:36.612382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:42.451601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:46.107475image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:49.862969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:54.963843image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:58.639468image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:02.639171image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:55.214349image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:05.892537image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:15.590073image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:20.362776image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:25.121153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:29.049328image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:32.747231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:37.066277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:42.712051image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:46.379384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:50.160492image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:55.217146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:58.928303image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:02.903991image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:55.989574image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:06.368270image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:16.082929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:20.612053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:25.386787image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:29.293538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:32.998914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:37.470350image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:42.951616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:46.630142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:50.430268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:55.450689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:59.183666image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:03.194432image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:56.862035image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:06.953118image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:16.523100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:20.878922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:25.652684image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:29.571635image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:33.269999image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:37.930817image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:43.242753image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:46.884804image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:50.701719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:55.712702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:59.448242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:03.448775image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:57.706446image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:08.113537image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:16.953267image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:21.140633image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:25.904869image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:29.824428image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:33.537457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:38.353736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:43.506397image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:47.145049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:51.021627image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:55.944326image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:59.713442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:59:03.731816image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:57:58.726386image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:09.505030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:17.408616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:21.403939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:26.186704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:30.096771image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:33.803355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:38.816194image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:43.775137image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:47.431742image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:51.444762image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:56.206968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-07-26T00:58:59.985926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-07-26T00:59:15.856760image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
AdministrativeAdministrative_DurationBounceRatesBrowserExitRatesInformationalInformational_DurationMonthOperatingSystemsPageValuesProductRelatedProductRelated_DurationRegionRevenueSpecialDayTrafficTypeVisitorTypeWeekend
Administrative1.0000.941-0.155-0.012-0.4340.3690.3640.050-0.0050.3280.4600.4210.0090.131-0.125-0.0120.0860.028
Administrative_Duration0.9411.000-0.164-0.023-0.4380.3570.3530.017-0.0070.3170.4300.4120.0190.064-0.132-0.0150.0070.000
BounceRates-0.155-0.1641.000-0.0470.6020.006-0.0030.0540.053-0.124-0.052-0.078-0.0180.1700.1350.0160.1230.050
Browser-0.012-0.023-0.0471.000-0.016-0.020-0.0130.0600.3750.0260.0440.0470.0550.0380.0210.0000.4720.059
ExitRates-0.434-0.4380.602-0.0161.000-0.186-0.2020.0570.023-0.308-0.519-0.476-0.0060.2450.1510.0210.1830.065
Informational0.3690.3570.006-0.020-0.1861.0000.9510.0300.0000.2190.3690.367-0.0230.078-0.054-0.0290.0280.011
Informational_Duration0.3640.353-0.003-0.013-0.2020.9511.0000.0150.0030.2260.3620.362-0.0150.068-0.056-0.0250.0070.000
Month0.0500.0170.0540.0600.0570.0300.0151.0000.0580.0210.0680.0460.0380.1750.2350.1600.1380.058
OperatingSystems-0.005-0.0070.0530.3750.0230.0000.0030.0581.000-0.0120.0210.0240.0270.0740.0230.0800.4650.118
PageValues0.3280.317-0.1240.026-0.3080.2190.2260.021-0.0121.0000.3420.3590.0010.413-0.070-0.0180.1100.031
ProductRelated0.4600.430-0.0520.044-0.5190.3690.3620.0680.0210.3421.0000.882-0.0210.127-0.022-0.0700.0790.000
ProductRelated_Duration0.4210.412-0.0780.047-0.4760.3670.3620.0460.0240.3590.8821.000-0.0100.073-0.051-0.0760.0350.004
Region0.0090.019-0.0180.055-0.006-0.023-0.0150.0380.0270.001-0.021-0.0101.0000.010-0.015-0.0040.1800.017
Revenue0.1310.0640.1700.0380.2450.0780.0680.1750.0740.4130.1270.0730.0101.0000.0860.1210.1040.028
SpecialDay-0.125-0.1320.1350.0210.151-0.054-0.0560.2350.023-0.070-0.022-0.051-0.0150.0861.0000.1100.0640.259
TrafficType-0.012-0.0150.0160.0000.021-0.029-0.0250.1600.080-0.018-0.070-0.076-0.0040.1210.1101.0000.3160.092
VisitorType0.0860.0070.1230.4720.1830.0280.0070.1380.4650.1100.0790.0350.1800.1040.0640.3161.0000.054
Weekend0.0280.0000.0500.0590.0650.0110.0000.0580.1180.0310.0000.0040.0170.0280.2590.0920.0541.000

Missing values

2024-07-26T00:59:04.170639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-26T00:59:05.061754image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-07-26T00:59:05.749797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
000.000.010.0000000.2000000.2000000.00.0Feb1111Returning_VisitorFalseFalse
100.000.0264.0000000.0000000.1000000.00.0Feb2212Returning_VisitorFalseFalse
200.000.010.0000000.2000000.2000000.00.0Feb4193Returning_VisitorFalseFalse
300.000.022.6666670.0500000.1400000.00.0Feb3224Returning_VisitorFalseFalse
400.000.010627.5000000.0200000.0500000.00.0Feb3314Returning_VisitorTrueFalse
500.000.019154.2166670.0157890.0245610.00.0Feb2213Returning_VisitorFalseFalse
600.000.010.0000000.2000000.2000000.00.4Feb2433Returning_VisitorFalseFalse
710.000.000.0000000.2000000.2000000.00.0Feb1215Returning_VisitorTrueFalse
800.000.0237.0000000.000000NaN0.00.8Feb2223Returning_VisitorFalseFalse
900.000.03738.0000000.0000000.0222220.00.4Feb2412Returning_VisitorFalseFalse
AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
1232000.0000.08143.5833330.0142860.0500000.0000000.0Nov2231Returning_VisitorFalseFalse
1232100.0000.060.0000000.2000000.2000000.0000000.0Nov1841Returning_VisitorFalseFalse
12322676.2500.0221075.2500000.0000000.0041670.0000000.0Dec2242Returning_VisitorFalseFalse
12323264.7500.0441157.9761900.0000000.0139530.0000000.0Nov22110Returning_VisitorFalseFalse
1232400.0010.016503.0000000.0000000.0376470.0000000.0Nov2211Returning_VisitorFalseFalse
123253145.0000.0531783.7916670.0071430.02903112.2417170.0Dec4611Returning_VisitorTrueFalse
1232600.0000.05465.7500000.0000000.0213330.0000000.0Nov3218Returning_VisitorTrueFalse
1232700.0000.06184.2500000.0833330.0866670.0000000.0Nov32113Returning_VisitorTrueFalse
12328475.0000.015346.0000000.0000000.0210530.0000000.0Nov22311Returning_VisitorFalseFalse
1232900.0000.0321.2500000.0000000.0666670.0000000.0Nov3212New_VisitorTrueFalse

Duplicate rows

Most frequently occurring

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue# duplicates
2100.000.010.00.20.20.00.0Mar2211Returning_VisitorFalseFalse11
3800.000.010.00.20.20.00.0May2213Returning_VisitorFalseFalse7
3000.000.010.00.20.20.00.0Mar3231Returning_VisitorFalseFalse6
1100.000.010.00.20.20.00.0Dec813920OtherFalseFalse5
3200.000.010.00.20.20.00.0May1113Returning_VisitorFalseFalse5
2900.000.010.00.20.20.00.0Mar3211Returning_VisitorFalseFalse4
5300.000.010.00.20.20.00.0Nov2211Returning_VisitorFalseFalse4
400.000.010.00.20.20.00.0Dec2211Returning_VisitorFalseFalse3
600.000.010.00.20.20.00.0Dec22113Returning_VisitorFalseFalse3
1200.000.010.00.20.20.00.0Feb3233Returning_VisitorFalseFalse3